Recombinant Golden hamster Il1a protein, His&Strep II-tagged

• Cat.No.: Il1a-4532G
• Product Overview: Recombinant Golden hamster Il1a protein(A0A1U7Q4M0)(1-269aa), fused with N-terminal His tag and C-terminal Strep II tag, was expressed in E.coli.

Specification

• Source: E.coli
• Species: Golden hamster
• Tag: His&Strep II
• Protein length: 1-269a.a.
• Form: If the delivery form is liquid, the default storage buffer is Tris/PBS-based buffer, 5%-50% glycerol. If the delivery form is lyophilized powder, the buffer before lyophilization is Tris/PBS-based buffer, 6% Trehalose, pH 8.0.
• Molecular Mass: 32.8 kDa
• AASequence: MAKVPDLFEDLKNCYSENEEYNSAI DHLSLSQKSFYDASYGSLHENCTDK FVSLRTSETSKMSSLTFEESLVMVA ATSDKGKILKKRRLGFNQAFAEDDL ETITRNLEETIQSDSAPYVFQSNMR YKLIRRVMQEFVLNDSLNQNIYLDA DQVHLKAASLNDLQHEVKFDMYVYS SEDDSKYPVTLKISNTQLFVSAQGE DQPVLLKEMPEIPKVITGSETDLIF FWKTVNSKNYFTSAAYPELFIATKE QSQVHLAMGLPSMTDFQIS
• Purity: Greater than 90% as determined by SDS-PAGE.
• Storage: Store at -20°C/-80°C upon receipt, aliquoting is necessary for mutiple use. Avoid repeated freeze-thaw cycles.
• Reconstitution: We recommend that this vial be briefly centrifuged prior to opening to bring the contents to the bottom. Please reconstitute protein in deionized sterile water to a concentration of 0.1-1.0 mg/mL.We recommend to add 5-50% of glycerol (final concentration) and aliquot for long-term storage at -20°C/-80°C.

Reviews

04/08/2021

High solubility.

07/02/2020

Good for intracellular staining.

03/13/2019

Effective in apoptosis assays.

Q&As

What methods are employed to dissect the intricate cross-talk between IL-1α and other cytokines, shedding light on its role in immune modulation?

Cross-talk between IL-1α's and other cytokines is dissected through methods such as co-immunoprecipitation, ELISA, and cytokine profiling arrays.

What experimental approaches allow researchers to dissect the paradoxical roles of IL-1α as both a pro-inflammatory and tissue repair mediator in distinct contexts?

IL-1α's paradoxical roles are dissected using conditional knockout mice, 3D culture systems, and molecular analyses to delineate context-specific effects.

How are cutting-edge techniques like single-cell RNA sequencing utilized to unravel the heterogeneity in IL-1α-responsive cell populations and their functional implications?

Single-cell RNA sequencing uncovers heterogeneity in IL-1α-responsive cell populations and their roles, revealing distinct molecular profiles and functions.

How is the intricate web of IL-1α's pro-inflammatory signaling pathways decoded using advanced experimental techniques?

IL-1α's intricate pro-inflammatory signaling pathways are decoded using advanced techniques like mass spectrometry, phosphoproteomics, and bioinformatics.

How are state-of-the-art genetic editing tools such as CRISPR-Cas9 applied to unravel IL-1α's precise contributions to inflammatory diseases?

Genetic editing tools like CRISPR-Cas9 unveil IL-1α's contributions to diseases by generating knockout models and studying resulting phenotypic changes.

How do researchers manipulate in vitro co-culture systems to dissect the dynamic interplay between immune cells and stromal cells in IL-1α-mediated responses?

In vitro co-culture systems are manipulated to study IL-1α-mediated responses, elucidating immune-stromal cell interactions via cytokine-specific neutralization.

What experimental strategies enable the identification of specific cellular receptors and downstream effectors responsible for IL-1α's diverse physiological effects?

Specific cellular receptors and effectors influenced by IL-1α are identified through techniques like co-immunoprecipitation, ChIP-seq, and siRNA knockdown.

How are sophisticated imaging techniques like live-cell microscopy harnessed to capture the real-time dynamics of IL-1α release and its impact on neighboring cells?

Live-cell microscopy captures real-time IL-1α release dynamics and its impact on neighboring cells, facilitated by fluorescent tagging and high-resolution imaging.

How is the quantitative relationship between IL-1α levels and disease progression established through longitudinal studies and statistical modeling?

Longitudinal studies and statistical modeling establish the quantitative relationship between IL-1α levels and disease progression, offering predictive insights.

How do multi-omics analyses, including transcriptomics and proteomics, provide a holistic view of the network of molecules influenced by IL-1α signaling?

Multi-omics analyses provide a holistic view of IL-1α signaling's impact, integrating transcriptomics, proteomics, and metabolomics data for comprehensive insights.